The data set needs to be preprocessed and formatted, using preprocess_data.py and make_dataset.py.
The -h flag will give the arguments needed.
Preprocessing is downcasing so that capitalization doesn't affect Morfessor.

Next, run train.py to train the model.
It will print statistics after each mini-batch.

python train.py <filename>.hdf5

Parameters like batch size, embedding dimension, and the number of epochs can be changed in the config.py file.

Last, word vectors can be output in the format word dim1 dim2 ..., with 1 word per line, via the output_word_vectors.py script.
Provide it a vocab of vectors to output, as well as a serialized network from training.